Model Theory of Stochastic Processes
Published on 9. April 2020
978-1-108-61926-4 (ISBN)
Description
Since their inception, the Perspectives in Logic and Lecture Notes in Logic series have published seminal works by leading logicians. Many of the original books in the series have been unavailable for years, but they are now in print once again. In this volume, the fourteenth publication in the Lecture Notes in Logic series, Fajardo and Keisler present new research combining probability theory and mathematical logic. It is a general study of stochastic processes using ideas from model theory, a key central theme being the question, 'When are two stochastic processes alike?' The authors assume some background in nonstandard analysis, but prior knowledge of model theory and advanced logic is not necessary. This volume will appeal to mathematicians willing to explore new developments with an open mind.
More details
Series
Language
English
Place of publication
Cambridge
United Kingdom
Target group
Professional and scholarly
Illustrations
Worked examples or Exercises; 1 Line drawings, black and white
File size
0,00 MB
ISBN-13
978-1-108-61926-4 (9781108619264)
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Schweitzer Classification
Persons
Sergio Fajardo works in the Department of Mathematics at the University of Los Andes, Bogota, Colombia. H. Jerome Keisler works in the Department of Mathematics at the University of Wisconsin, Madison.
Content
Introduction; 1. Adapted distributions; 2. Hyperfinite adapted spaces; 3. Saturated spaces; 4. Comparing stochastic processes; 5. Definability in adapted spaces; 6. Elementary extensions; 7. Rich adapted spaces; 8. Adapted neometric spaces; 9. Enlarging adapted spaces; References.
